An Approach to Track and Analyze the Trend of Antimicrobial Resistance Using Python: A Pilot Study for Anand, Gujarat, India-May 2022-August 2023.

The present work deals with the analysis and monitoring of bacterial resistance in using Python for the state of Gujarat, India, where occurrences of drug-resistant bacteria are prevalent. This will provide an insight into the portfolio of drug-resistant bacteria reported, which can be used to track resistance behavior and to suggest a treatment regime for the particular bacteria. The present analysis has been done using Python on Jupyter Notebook as the integrated development environment and its data analysis libraries such as Pandas, Seaborn, and Matplotlib. The data have been loaded from excel file using Pandas and cleaned to transform features into required format. Seaborn and Matplotlib have been used to create data visualizations and represent the data inexplicable manner using graphs, plots, and tables. This program can be used to study disaster epidemiology, tracking, analyzing, and surveillance of antimicrobial resistance with a proper system integration approach.

Mutations in V84I & A184V of blaTEM cluster plays a pivotal role in the dynamics of Ω-loop leading to genesis of IR-TEM.

The Enterobacteriaceae family exhibits resistance to antibiotics by producing ß-Lactamase. Mutations in ß-Lactamase, have led to the generation of inhibitor resistant variants known as IR-TEM. In the present study, IR-TEM ß-Lactamase of Enterobacter hormaechei and Enterobacter asburiae was compared. To investigate the mechanism behind the conferred mutation, we studied its interaction with Clavulanic acid, (ß-Lactamase inhibitor) with different lineages of TEM and IR-TEM. We found that Clavulanic acid quickly left the binding pockets of both variants using molecular dynamics (MD) simulations. Interestingly, mutations at the V84I and A184V positions were found to drastically influence the protein dynamics. Mutating the residues at V84I and A184V positions by computational mutagenesis in Enterobacter hormaechei, it was observed that the residues on the Ω-loop as well as a few downstream residues were primarily involved in generating resistance towards inhibitors by conferring increased flexibility to the loop. This further strongly supports the notion that inhibitor resistance in ß-Lactamase is conferred through allosteric regulation, wherein mutations in positions 84 and 184 may play an important role in regulating the movement of the Ω-loop. These two positions determine the lineage pattern between two clusters in TEM-1 and TEM-116. To date, no reports have been made regarding the importance of these mutations and their dynamics in Ω-loop.Communicated by Ramaswamy H. Sarma.

Computational drug re-purposing targeting the spike glycoprotein of SARS-CoV-2 as an effective strategy to neutralize COVID-19.

COVID-19 has intensified into a global pandemic with over a million deaths worldwide. Experimental research analyses have been implemented and executed with the sole rationale to counteract SARS-CoV-2, which has initiated potent therapeutic strategy development in coherence with computational biology validation focusing on the characterized viral drug targets signified by proteomic and genomic data. Spike glycoprotein is one of such potential drug target that promotes viral attachment to the host cellular membrane by binding to its receptor ACE-2 via its Receptor-Binding Domain (RBD). Multiple Sequence alignment and relative phylogenetic analysis revealed significant sequential disparities of SARS-CoV-2 as compared to previously encountered SARS-CoV and MERS-CoV strains. We implemented a drug re-purposing approach wherein the inhibitory efficacy of a cluster of thirty known drug candidates comprising of antivirals, antibiotics and phytochemicals (selection contingent on their present developmental status in underway clinical trials) was elucidated by subjecting them to molecular docking analyses against the spike protein RBD model (developed using homology modelling and validated using SAVES server 5.0) and the composite trimeric structures of spike glycoprotein of SARS-CoV-2. Our results indicated that Camostat, Favipiravir, Tenofovir, Raltegravir and Stavudine showed significant interactions with spike RBD of SARS-CoV-2. Proficient bioavailability coupled with no predicted in silico toxicity rendered them as prospective alternatives for designing and development of novel combinatorial therapy formulations for improving existing treatment regimes to combat COVID-19.